Results 251 to 260 of about 425,331 (287)

A stochastically-generated auto-regressive model

Proceedings of the 33rd Midwest Symposium on Circuits and Systems, 2002
A summary is presented of new work related to an adaptive stochastic filter that is used to generate an auto-regressive model for an unknown system. Simulations are presented that show the convergence on the unit circle of the adaptive poles to the optimum poles. >
D.M. Etter, B.S. Chia
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Stochastic regression modeling of chemical spectra

Chemometrics and Intelligent Laboratory Systems, 2014
Abstract A stochastic regression model is presented that separates signal from noise in chemical spectra. Spectra are decomposed into additive contributions from signal and from estimated noise. Numerical results on sample spectra are presented and suggest that this strategy offers an effective and computationally efficient framework for ...
Anthony J. Kearsley, Yutheeka Gadhyan, William E. Wallace   +2 more
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On stochastic linear regression model selection

AIP Conference Proceedings, 2019
The research article primarily focuses on the criteria for selecting best stochastic linear regression model namely Cp - conditional mean square error prediction, Generalized Mean Squared Error criterion (GMSE) which comes out of the deficiencies of R2 and R¯2 criteria.
J. Peter Praveen, B. Mahaboob, Ranadheer Donthi, S. Vijay Prasad, B. Venkateswarlu   +4 more
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Stochastic Algorithms in Estimating Regression Models

1996
The optimization problem may be formulated as follows: For a given objective function f: Ω → R, Ω⊂ R d, the point x* is to be found such that $$f\left( {{\rm{x*}}} \right) = \mathop {\min }\limits_{{\rm{x}} \in \Omega } f\left( {\rm{x}} \right).$$ It is evident that the point x* represents the global minimum of real-valued function f (of d ...
Ivan Krivý, Josef Tvrdík
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Stochastic Approximation and Nonlinear Regression

Technometrics, 1969
W. T. Federer, A. E Albert, L. A. Gardner   +2 more
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Singular Ridge Regression With Stochastic Constraints

Communications in Statistics - Theory and Methods, 2013
This article considers the estimation of the restricted ridge regression parameter in singular models. The problem is commenced with considering elliptically contoured equality constrained and then followed by proposing the preliminary test estimator.
M. Arashi, M. Janfada, M. Norouzirad
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Stochastic and non-stochastic covariates in binary regression

2020
BAĞIMSIZ DEĞİŞKENLERİN S TO KASTİ K VE STOKASTİK OLMADIĞI DURUMLARDA İKİLİ REGRESYON Evrim Oral Hacettepe Üniversitesi, İstatistik Bölümü, İstatistik Teorisi Anabilim Dalı ÖZ Olabilirlik denklemlerinin çözümleri genellikle sorunludur, dolayısıyla da en çok olabilirlik tahmin edicilerinin elde edilmesi zordur. 1967 yılında M. L. Tiku, bu zorluğu ortadan
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Stochastic Parameter Regression Model

Journal of Marketing Research, 1986
Eric R. Ziegel, P. Newbold, T. Bos
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Local Regression and Stochastic Approximation

ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 1973
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Chapter 14. Stochastic-Regression

2023
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